The changing role of CIO and intelligent automation’s impact.

With the ever-increasing volume and complexity of data coming in (thanks in large part to trends like the IoT, BYOD and, of course, Big Data), the role of the CIO has also begun to rapidly evolve over the past decade or so. These individuals are now facing pressures to keep infrastructure updated as well as analyze and leverage the data available to them for the benefit of the organization, and all while keeping costs down and internal networks, systems, applications and information secure. This is no easy feat, but thanks to intelligent automation, it is entirely achievable.

Due to the heavy volume of data being shared today, integrating automated workflows and processes has become increasingly necessary in order to analyze and derive value from that data, and in a way that is as cost-effective as possible. If IT departments are to remain relevant, drive efficiency and support a profitable operation, it is imperative that they employ the use of intelligent automation, and with the CIO as the key decision maker, it’s up to him or her to ensure that the right resources are in place.

As recently as just a few short years ago, the general public was becoming aware of the IoT, but today organizations of every size and industry are capturing insight and achieving real, sustainable ROI from this advanced (and ever-evolving) technology. Furthermore, intelligent automation is virtually revolutionizing everything from the SOC and NOC to the service desk and data center. Intuitive technology and artificial intelligence are being utilized to proactively monitor systems and devices, gather and evaluate complex data, remediate incidents and resolve issues – in many cases before any human worker is even made aware.

As a result of all of these changes, more basic requests, like password resets and system refreshes, which used to be handled almost exclusively by L1 support professionals are now being shifted to intelligent automation technology. Self-service chatbots are empowering the end-user like never before while simultaneously alleviating IT personnel of the heavy burden associated with these routine, repetitive (but necessary) tasks.

Of course, this hasn’t necessarily made life perfect for IT professionals. Increased consumerization of IT has resulted in the services of many IT departments being compared and contrasted against that of external service providers. Expectations of faster service and the demand to take on more while also minimizing costs as much as possible continue to rise, subsequently increasing the pressures on top IT personnel. Perhaps no one is feeling the pressures of these demands more than the CIO. Embracing intelligent automation is no longer an option, but a critical requirement.

At the same time, the IT world is witnessing a significant change in responsibilities for the CIO, shifting from the old way of the maintenance and provision of physical infrastructure and devices to more of a data management role with an emphasis on innovating and creating value. Digitalization is now the focus, with CIOs playing a lead role in developing and implementing it throughout the entire enterprise. Paradoxically, these high-level IT professionals are being forced to orient and align themselves more with value creation than the efficiency that once defined them.

Data analytics is now being hailed as one of the primary contributors to driving this value, particularly given the ever-increasing pool of available information. It’s important to point out, however, that CIOs and other top IT managers must take the time necessary to understand what data is available to them, what that data equates to and, most importantly, how they can best leverage that information to improve operations across all functions of the organization. Savvy CIOs will leverage intelligent automation to obtain key insights that will support current and future business goals as well as identify new insight and make data-driven decisions that will give the company competitive advantage.

Finally, the evolving role of the CIO will involve more engagement, inspiration and education of others than ever before. To fulfill these duties, it’s absolutely essential that the CIO develops into a strong visionary and consistent innovator for the organization. Through better data analysis and the more widespread use of intelligent automation, those in this important role will begin to morph into the position of strategic advisor, driving the business onward and upward toward increasing and sustainable success well into the future.

Are you a CIO that is struggling to adapt to your changing role? Intelligent automation, powered by AI and machine learning, could provide the foundation upon which you can continue to build your career and your legacy.

Experience the power of Next-Gen Intelligent Automation today!

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3 Ways NOT Automating Could Cost Your Business (Big Time)

Industry experts frequently point out the many ways leveraging intelligent automation can benefit an organization. For instance, increased efficiency levels, lower expenditure, scalability and the ability to do more with less all top the list. What we don’t often mention, however, is the flipside. That is, the impact NOT automating could potentially have on a company’s ongoing success and future profitability. In fact, failing to automate can come at a substantial cost in three specific areas. Here’s how.

Human Error

As the IT realm continues to become more complex, the risk of errors by the individuals responsible for handling fundamental tasks and workflows will inevitably increase. These errors can be costly in a number of ways, including impact to both internal departments as well as clients, and potential loss of business. These costs can be further compounded by the amount of time it takes the IT department to correct said errors.

To gain a clearer picture of exactly how much human error can cost your organization, take some time to document all the recent mistakes your IT team has made and then assign a dollar value to each of those errors. You may be surprised at how much those losses can truly add up. What’s more, the larger your organization grows, the more complex your infrastructure will become, which means an even greater risk of IT errors. Intelligent automation dramatically reduces, and in most cases, entirely eliminates human error, ensuring a more efficient and effective operation overall.

Employee Turnover

Recent data estimates that replacing an employee can cost a business up to 33% of that person’s annual salary. To put this into perspective, let’s say you pay your average IT support technician a salary of $45,000 per year. If that employee quits, it could cost you up to $15k just to find someone to find their replacement. That’s an incredible waste of money.

In the IT field, however, turnover is a serious problem, the biggest reason for which is employee burnout. Being on call 24/7 may be par for the course, but those 2am phone calls get old real quick. Furthermore, having staff on-hand to monitor, maintain and update your infrastructure around the clock isn’t practical, nor is it typically feasible.

By introducing intelligent automation into the mix, you’ll alleviate much of the unnecessary burden from your IT team. They’ll be able to focus their efforts on more meaningful work, which will keep them engaged and happy. In turn, they’ll be more likely to recommend you as a good employer to their own networks, which could help you recruit additional talent when it comes time to scale.

Missed Opportunities

Tying in directly with the two points listed above is the third way lack of automation can cost your business: missed opportunities. When employees are bogged down with manual, repetitive and boring tasks, not only will they not have the time or energy to work on other, more meaningful projects, but if they’ve got one foot out the door, they probably won’t care much about your company’s success anyway.

Likewise, when human errors are causing issues with the current way your organization operates, it can stagnate your chances to scale and grow. In other words, your IT team will be so busy putting out fires and trying to recover from costly mistakes, they won’t have the time or energy to dedicate to other value-added and mission-driven activities.

If you want your company to be able to compete in the digital age, you need employees who are ready, willing – and most importantly – able to innovate. Intelligent automation complements human workers by doing much of the heavy lifting while enabling better decision-making and freeing up employees to fully utilize their cognitive abilities. This creates a “best of both worlds” scenario where everyone benefits.

So, can intelligent automation save your company money, make your operations more efficient and provide other valuable benefits? Absolutely. But it’s equally as important to consider what the real costs are of not automating. The question you should be asking isn’t should you automate, but rather can you really afford not to.

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Helping the IT Help Desk – What you Need to Know about Virtual Support Agents

What you Need to Know about Virtual Support Agents

This post was originally published as a guest article on InsideBIGDATA.

IT help desks everywhere are handling a growing number of requests from multiple channels every day. And the more time the service desk spends putting out fires by phone, through email, or in person, the less time they have to focus on resolving the bigger issues and applying their cognitive skills to more meaningful projects.

Are chatbots or virtual support agents the answer? The success of virtual support depends on several key factors. Here’s how to identify those factors and evaluate whether or not VSAs are right for your organization.

Chatbot vs. VSA

The first important piece of the puzzle is understanding the difference between chatbot and virtual support agent technology. While the concept is similar, there is a distinct and critical difference, particularly as it relates to use in the help desk arena. This difference can be summed up in one word: context.

If you’ve ever visited a website and used the “live chat” feature to ask a question, chances are the party you interacted with was a chatbot. And chances are even greater that the responses you received were basic and scripted based on a set of common inquiries. Simply put, chatbots are one-dimensional. They cannot engage beyond the basic communication that they’ve been programmed for.

Virtual support agents, on the other hand, when set up properly, have far greater functionality and flexibility than chatbots. Thanks to underlying technologies like artificial intelligence, machine learning and natural language processing, VSAs are capable of understanding the meaning and intent behind human communication, even if it’s vague or ambiguous.

In other words, VSAs can understand context. As such, they are able to hold realistic conversations, generate authentic dialogue and provide intelligent responses based not only on the data they’ve received (like chatbots), but also on the context of that data.

VSAs and the Help Desk

As mentioned, help desk agents field a mind-boggling volume of incoming requests, the majority of which are routine and repetitive in nature, but important nonetheless. For instance, password resets are a necessary evil in the IT support realm as they are required in order to keep others in the organization productive.

Yet, the process of manually resetting user passwords is not only a tremendous waste of human resources, but it’s also a massive waste of money. In fact, Forrester Research estimates that the average cost of a single password reset is $70. Multiply that cost by the number of times your support team executes this task and it really adds up.

That’s where virtual support technology comes in. VSAs enable the help desk to automate almost all routine, repetitive and manual tasks. Beyond this, however, is where the true value of virtual support becomes evident. In addition to automating the basics, the technology behind VSAs enables them to work alongside human agents, providing the same level of support and assistance.

How it works is remarkably simple. The virtual agent pulls data from various knowledge management resources to respond intelligently to incoming requests. Virtual agents are also capable of taking action on behalf of the end-user without the need for human intervention. This means fewer escalations and a more manageable workload so human support agents can focus their skills on more meaningful business initiatives.

The Key to Success

Of course, as with any technology, virtual support agents do require work in order to set them up properly. For instance, AI and NLP technologies are essential components to VSA functionality. The most fundamental key to success, however, is the establishment and maintenance of a comprehensive, dynamic knowledge-base. After all, this is the resource from which the VSA will draw its responses. Without in-depth and accurate data, virtual agents will not be capable of operating to their fullest potential.

Gartner predicts that by 2023, 40% of I&O teams will be using AI-augmented automation, resulting in higher productivity with greater agility and scalability. Given the current benefits, coupled with the promise of improving technology, it’s not a stretch to see that VSAs will continue to play an increasing role in making the help desk experience better for everyone.

Click here to view the original post on InsideBIGDATA.

Still holding out on IT automation? Here are 4 signs the time has come.

stop resisting IT automation

IT automation is certainly not a new concept. In fact, it’s been in use to some degree for over a century. Yet, there are still a great number of enterprise-level organizations that are on the fence about whether this advanced technology is really worth investing in. If you are one of these late bloomers and are still unsure of whether or not you should take the plunge and employ intelligent IT automation in your company, here are four signs that will let you know it’s time.

Your IT department is struggling to deliver services in a timely, efficient manner.

When a ticket gets opened to IT, how long does it take to achieve satisfactory resolution? In today’s fast-paced business environment, regardless of what industry you are in, agility and efficiency are absolutely critical to ongoing success and future growth. If the demands of your workforce are becoming too much for your skilled IT personnel to handle, the time to leverage technology has come. Not only will IT automation alleviate the burden of many of the day-to-day repetitive tasks, but it will also free up your talented technicians to apply their valuable skills in a more resourceful and profitable manner.

You have way too many staff members on hand just to handle those peak cycles.

Optimized resource allocation is the key to running a lean, profitable operation. If you have far too many IT employees on the payroll just so you can ensure smooth workflow during peak cycles, you are undoubtedly wasting money the rest of the year. Conversely, if your current IT department becomes completely overwhelmed during those peak cycles, your capacity is too low and you’re likely to see higher employee turnover rates. IT automation provides the ability to scale up or down as needed without having to make any changes to your human workforce.

Your employees are wasting an incredible amount of time and effort on repetitive tasks.

Even if you feel that your operation is being managed at the appropriate capacity and the turnaround time of your IT department is acceptable, if your IT team is spending the majority of their day completing manual tasks and processes, you’re wasting money and missing out on opportunity. You’re also facing a much higher risk of costly human error. Why not let artificial intelligence handle these simple, routine tasks? That way you’ll be paying an appropriate salary to workers who are able to better utilize their valuable skillset and the work will be completed faster and more accurately.

Your legacy systems and applications are operating independently.

Of course it doesn’t make sense to invest in an entire system overhaul, but what kind of operation are you running if every application you’ve got in place is functioning in its own silo. The problem many organizations face is the fact that legacy systems which offer useful benefits individually don’t have the capability of working together. This leads to tremendous inefficiency. The beauty of most modern IT automation and orchestration platforms is that they are designed to integrate existing systems, platforms and applications to create a more cohesive and streamlined infrastructure. This allows the organization to avail itself of all the benefits of each legacy system as they work in tandem, complementing and enhancing each other’s capabilities.

If you can relate to any of the four challenges listed above, the time to consider adopting intelligent IT automation is now. Get started today with your free 30 day trial and see for yourself what you’ve been missing out on.

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4 Tech Trends to Watch for in 2020

4 Tech Trends to Watch for in 2020Technology has been evolving since the dawn of time. As we prepare to enter another new decade, we can expect to see even more accelerated change on the tech front. With so much happening so remarkably quickly, it can be difficult to know which trends to track. To narrow things down, we’ve rounded up the top four adaptations that we believe will bring the greatest innovation and growth in 2020 and beyond. Take a look below.

Intelligent Automation

Not surprisingly, intelligent automation topped our list of technologies that will drive progress and success over the next several years. Thanks to the growing proliferation of cloud computing, big data and increasingly “smart” robotics, the future is a place where automation will no longer be an option, but rather a necessity. Leveraging these highly advanced technologies will enable organizations in every industry to streamline operations, maximize efficiency and uptime, dramatically lower costs and remain competitive.

Intuitive AI

While artificial intelligence plays a role in the big-picture automation trend, its capabilities and ongoing advancements warrant a separate mention on this list. The computers of tomorrow will be able to learn and evolve much the same way we do, which means that in addition to increased computing power, AI will be able to carry out tasks that were once reserved for humans and at a lightning speed. Underlying technologies, like machine learning, facial recognition and natural language processing will enable AI to continue to learn and grow smarter without the need for human intervention.

Voice Command

We’ve already begun seeing rapid and advancing developments in voice technology, thanks to the increasing adoption of voice assistants, like Siri and Alexa. Over the coming months and years, expect to see voice technology continue to develop and improve, particularly in the way of its ability to interpret and understand the context of the spoken word. This is where NLP will really begin to have a significant impact on our day to day lives.

Analytics

Enterprises across the globe are already leveraging analytics as a key driver of growth and innovation. Not only can analytics confirm whether you are successful in your industry, but they can help predict which direction the market will likely head in over the coming months and years. Data processing, facilitated by AI and machine learning, will continue to be used to turn massive amounts of information into actionable insights, as well as identifying issues and recommending next steps.

Without question, we are entering an exciting era in technological advancement. The most exciting part is that you don’t have to wait until next year to experience the power of these amazing tech trends. Download your free 30 day trial of Ayehu today and put the power of intelligent automation, powered by AI and machine learning, to work for you! Click here to get started.

How is AIOps Really Used in IT?

How is AIOps Really Used in IT?

Digital transformation has simultaneously simplified and added a layer of complexity to the modern world of IT operations. Managing multiple environments across a number of locations invoked the need to introduce several disparate tools and platforms, leaving IT siloed and, oftentimes, overwhelmed. This has perpetuated the need for artificial intelligence for IT operations, or AIOps for short. For those not yet leveraging AIOps, or who are still in the beginning stages, here are three real-world, value-added use cases to consider.

Threat Detection – AIOps is the perfect complement to a security management strategy because its machine learning algorithms are capable of mining massive amounts of data for scripts, botnets and other threats or anomalies that could potentially harm a network. This is especially true for threats that are complex and sophisticated, which is why it’s such a valuable addition.

Intelligent Alerting – Today’s ITOps teams are being inundated with alerts of which only a small portion are actually critical. AIOps can manage these alerts autonomously, evaluating, identifying core issues, prioritizing and either escalating or remediating them without the need for human intervention. Imagine trimming that overflowing inbox of alerts down to just one or two that truly matter.

Capacity Optimization – Through the use of AI-based statistical analysis, IT operations teams can optimize application workloads and availability across the entire infrastructure. This technology is capable of proactively monitoring bandwidth, utilization, CPU, memory and much more, with the goal of maximizing application uptime. AIOps can also be used for predictive capacity planning.

Of course, this is really just the beginning. As environments become increasingly complex and technology options continue to grow, IT operations teams will find themselves under even more pressure to deliver maximum business value with minimal downtime. AIOps emerges as the ideal solution, facilitating infrastructure monitoring and management that is much faster and far more efficient. It’s no surprise, that IT leaders and other key decision-makers are starting to take notice.

Today, AIOps is all about threat management, streamlined alerting and maximizing uptime. Tomorrow, IT automation powered by artificial intelligence, machine learning and natural language processing technology is positioned to forge entirely new pathways for innovation and growth. In other words, the journey has just begun and the future is beaming with possibility.

Want to get in on the ground floor? Grab your free 30-day trial of Ayehu NG and put the power of AIOps to work for your organization.

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Bridging the NOC and SOC for an Integrated IT Powerhouse

The similarities between the role of the Network Operation Center (NOC) and Security Operation Center (SOC) often lead to the mistaken idea that one can easily handle the other’s duties. Furthermore, once a company’s security information and event management system is in place, it can seem pointless to spend money on a SOC. So why can’t the NOC just handle both functions? Why should each work separately but in conjunction with one another? Let’s take a look a few reasons below.

First, their roles are subtly but fundamentally different. While it’s certainly true that both groups are responsible for identifying, investigating, prioritizing and escalating/resolving issues, the types of issues and the impact they have are considerably different. Specifically, the NOC is responsible for handling incidents that affect performance or availability while the SOC handles those incidents that affect the security of information assets. The goal of each is to manage risk, however, the way they accomplish this goal is markedly different.

The NOC’s job is to meet service level agreements (SLAs) and manage incidents in a way that reduces downtime – in other words, a focus on availability and performance. The SOC is measured on their ability to protect intellectual property and sensitive customer data – a focus on security. While both of these things are critically important to the success of an organization, having one handle the other’s duties can spell disaster, mainly because their approaches are so different.

Another reason the NOC and SOC should not be combined is because the skillset required for members of each group is vastly different. A NOC analyst must be proficient in network, application and systems engineering, while SOC analysts require security engineering skills. Furthermore, the very nature of the adversaries that each group battles differs, with the SOC focusing on “intelligent adversaries” and the NOC dealing with naturally occurring system events. These completely different directions result in contrasting solutions which can be extremely difficult for each group to adapt to.

A new set of problems arise, however, when the two teams become siloed, with each group focused on only half of the equation. The resulting gap, particularly in terms of data that is not being shared, perpetuates an even broader gap in the necessary knowledge to maximize the effectiveness of each team. Efforts by the SOC that fail to take into account operational requirements or efficiencies cause bottlenecks that can result in a disruption in network performance. Likewise, fingers can be pointed at the NOC for implementing network designs that leave critical resources exposed and vulnerable.

The best solution is to respect the subtle yet fundamental differences between these two groups and leverage a quality automation product to link the two, allowing them to collaborate for optimum results. The ideal system is one where the NOC has access to the SIEM, so they can work in close collaboration with the SOC and each can complement – rather than impede – the other’s duties. The SOC identifies and analyzes issues, then recommends fixes to the NOC, who analyzes the impact those fixes will have on the organization and then modifies and implements accordingly.

So, what’s the best way to achieve this cross-functional collaboration and optimization? The most important goal is to eliminate operational and/or technical silos. By leveraging a cross-silo intelligent automation platform, security incidents can be detected and resolved while events simultaneously trigger automatic changes both to security as well as network device configurations. This essentially closes the loop on cyberattack mitigation while effectively bridging the distance between security and ops teams.

As the IT environment introduces increasingly complex applications and workflows across a spectrum of systems and devices, and oftentimes in a variety of different locations, the demand for a more streamlined, holistic approach also continues to grow. The time has come to rethink the way the NOC and SOC work together. With an orchestrated approach, powered by intelligent automation, organizations will be able to close the gap between the two departments to more effectively address today’s multifaceted threats, regardless of where they happen to occur within the network.

Ayehu NG is an intelligent IT Automation and Orchestration platform built for the digital era. As an agentless platform, Ayehu is easily deployed, allowing organizations to rapidly automate tasks and processes, including interoperability across disparate solutions and systems, all in one, unified platform.

If you’re ready to bridge the gap between your NOC and SOC to create an integrated IT powerhouse, click here to start your free trial.

Solving your “what if” scenarios with intelligent automation

When it comes to convincing businesses that intelligent automation is the way of the future, the biggest objection to overcome is the age-old question, “what if….” Many IT professionals and other key decision makers within an organization carry the fear that automated tasks which are put in place to solve a problem may actually end up causing more harm than good.

What could go wrong? What if the whole thing blows up in our faces and we end up with an even bigger mess on our hands? The answer is simple: when automation is designed and tested properly, everything should work out just as it is planned, and the results will be well worth the effort.

Creating and Designing Your Workflow

The first step in setting up intelligent automation so that it works properly is creating and designing your workflows. You have to have your end result in mind, and then figure out the steps necessary to achieve that end result. Various criteria will need to be identified, so that you know whenever a certain function or task occurs, the next step in the workflow will automatically be triggered. So, to summarize, establish your desired end result, and then develop a list of steps to help you achieve that result. List each criterion in the process and determine what next step each criterion would trigger.

Testing 123…

The next important step, once you’ve created your workflow, is to try it out in a controlled environment. Test each step in the process to verify that the desired result for each is achieved. If something isn’t working properly, re-evaluate to determine why and then work to fix that piece until the entire process is functioning correctly. We recommend starting small and testing a variety of situations and scenarios to really be sure everything is working properly. Continue this process until you are confident that your automated workflow is working precisely as it should.

Implement

Once you’ve tested your automated workflow enough to be confident that it’s functioning as it is meant to function, it’s time to put it into action. It can be a bit nerve wracking to implement a workflow for the first time live, but once you see it in action, you’ll become that much more confident that it will be there to meet your needs whenever necessary.

Call on the Experts

If, at any time during the above outlined process, you feel as though you’re not getting the results you’re looking for, or you need some guidance and support, don’t be afraid to reach out to the experts. Remember, part of choosing the right intelligent automation product is choosing a company that offers plenty of training and support to its customers. Any company will be there for you when you’re in the process of making a purchasing decision, but you want to make sure that you choose someone that will also be there for you after the fact. If you’re feeling overwhelmed or just have a few questions, don’t be afraid to reach out to your software partner for assistance.

The hands-off nature of intelligent automation can make some professionals feel uneasy. They may wonder if the very system that’s being put in place to solve a particular problem within the organization will actually end up causing more harm than good. The truth is when you know the steps to take, and you’re careful to work through each step just as you should, the result will be exactly what you’re hoping for. When automation is created, developed, tested and supported properly, there is no longer the need to ask “what if”, but rather “why did I wait so long to do this?”

What are YOU waiting for? Contact us or better yet – download your free trial today to start leveraging intelligent automation for your organization.

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Transform Your Organization with AI in 5 Steps

According to IDG’s 2018 State of the CIO report, 73% of IT executives struggle with striking a balance between the need to innovate and the demand to achieve operational excellence. One of the main reasons for this is the fact that IT frequently gets bogged down with a growing list of tools and competing priorities, all of which chip away at precious time and available resources. As a result, more organizations are turning to artificial intelligence as a way to bring technology, data and people together to drive digital transformation. Here’s how you can use AI to do the same in five easy steps.

Step 1: Understand what you can and cannot solve.

While AI has the potential to transform an entire organization, machine learning technology is not yet capable of fully replacing the experience of skilled professionals. Instead, IT teams can leverage automation powered by artificial intelligence to free up skilled workers to do what they do best: apply their expertise to develop solutions for highly prioritized issues.

Machine learning algorithms can sift through mountains of data to spot trends, deliver insights and identify potential solutions. Automation can assist in resolving certain issues. But it’s up to the IT department to apply the deep analysis necessary to achieve business goals.

Step 2: Identify and prioritize problems to address.

Artificial intelligence can help address the two biggest IT challenges: maximizing operational efficiency and improving the customer experience. The role of CIO has taken on much greater importance, with 80% of businesses viewing IT managers as strategic advisors for the business. As such, these individuals, along with others in IT, are responsible for defining key areas of focus for new technology, such as AI solutions. In order to achieve buy-in, new solutions should be presented in a way that closely aligns with broader organization-wide goals.

Step 3: Pinpoint gaps in technology and skills.

The IT skills gap is an ever-present problem, and it doesn’t appear to be going away any time in the near future. In addition to the talent shortage, IT budgets are stagnating. AI solutions can help to mitigate both of these issues by empowering IT teams to do more with less, and at a much faster rate than they could on their own.

Keep in mind, of course, that key skills are still necessary in order to drive these solutions. To address this, many organizations are looking to reskill existing staff. Thankfully, today’s automation tools do not require a PhD to operate them. Regardless, decision-makers should look for a data-based platform that features AI-powered technology.

Step 4: Develop your strategy.

Once you’ve identified which problems AI is capable of solving for your organization, defined the specific challenges you’d like to overcome, achieved buy-in for adoption and assessed what resources you have to work with, the four step is to develop your strategy for deployment. This strategy should include the following main segments:

  • Roadmap – from proof of concept to continuous process improvement
  • Testing Plan – defining what you want to accomplish and what metrics will indicate progress
  • Team – investing in and arranging training for IT staff

Step 5: Prepare for scale.

Any broader AI strategy should involve mapping out data across all systems, services, apps and infrastructure. This includes both structured and unstructured data as well as data in a variety of different formats. It’s essential to select a solution that is capable of ingesting, normalizing and formatting all data sources for analysis.

Further, it’s critical to choose a platform that offers room to mature and scale. And keep in mind, also, that while the “land and expand” concept may work for some companies, others – particularly those with a higher risk tolerance – may be better off to push transformation across the entire organization at once. Generally speaking, however, stable and sustainable change begins by starting small and building on early successes. The key is leaving enough room to grow.

Want to experience some of those early successes now? Launch your free 30-day trial of Ayehu NG and put the power of AI and intelligent automation to work for your organization today!

How to Leverage Intelligent Automation to Better Manage Alert Storms [Webinar Recap]

Author: Guy Nadivi

As most of you already know, there’s a digital transformation underway at many enterprise organizations, and it’s revolutionizing how they do business. That transformation though is also leading to increasingly more complex and sophisticated infrastructure environments. The more complicated these environments get, the more frequently performance monitoring alerts get generated. Sometimes these alerts can come in so fast and furious, and in such high volume, that they can lead to alert storms, which overwhelm staff and lead to unnecessary downtime.

Since the environments these alerts are being generated from can be so intricate, this presents a multi-dimensional problem that requires more than just a single-point solution. Ayehu has partnered with LogicMonitor to demonstrate how end-to-end intelligent automation can help organizations better manage alert storms from incident all the way to remediation.

The need for that sort of best-of-breed solution is being driven by some consistent trends across IT reflecting a shift in how IT teams are running their environments, and how costly it becomes when there is an outage. Gartner estimates that:

Further exacerbating the situation is the complexity of multi-vendor point solutions, distributed workloads across on-premise data centers, off-premise facilities, and the public cloud, and relentless end-user demands for high availability, secure, “always-on” services.

From a monitoring standpoint, enterprise organizations need a solution that can monitor any infrastructure that uses any vendor on any cloud with any method required, e.g. SNMP, WMI, JDBC, JMX, SD-WAN, etc. In short, if there’s a metric behind an IP address, IT needs to keep an eye on it, and if IT wants to set a threshold for that metric, then alerts need to be enabled for it.

The monitoring solution must also provide an intuitive analytical view of the metrics generated from these alerts to anyone needing visibility into infrastructure performance. This is critical for proactive IT management in order to prevent “degraded states” where services go beyond the point of outage prevention.

This is where automating remediation of the underlying incident that generated the alert becomes vital.

The average MTTR (Mean Time To Resolution) for remediating incidents is 8.40 business hours, according to MetricNet, a provider of benchmarks, performance metrics, scorecards and business data to Information Technology and Call Center Professionals.

When dealing with mission critical applications that are relied upon by huge user communities, MTTRs of that duration are simply unacceptable.

But it gets worse.

What happens when the complexities of today’s hybrid infrastructures lead to an overwhelming number of alerts, many of them flooding in close together?

You know exactly what happens.

You get something known as an alert storm. And when alert storms occur, MTTRs degrade even further because they overwhelm people in the data center who are already working at a furious pace just to keep the lights on.

If data center personnel are overwhelmed by alert storms, it’s going to affect their ability to do other things.

That inability to do other things due to alert storms is very important, especially if customer satisfaction is one of your IT department’s major KPI’s, as it is for many IT departments these days.

Take a look at the results of a survey Gartner conducted less than a year ago, asking respondents what they considered the most important characteristic of an excellent internal IT department.

If an IT department performed dependably and accurately, 40% of respondents considered them to be excellent.

If an IT department offered prompt help and service, 25% of respondents considered them to be excellent.

So if your IT department can deliver on those 2 characteristics, about 2/3 of your users will be very happy with you.

But here’s the rub. When your IT department is flooded with alert storms generated by incidents that have to be remediated manually, then that’s taking you away from providing your users with dependability and accuracy in a prompt manner. However, if you can provide that level of service regardless of alert storms, then nearly 2/3 of your users will consider you to be an excellent IT department.

One proven way to achieve that level of excellence is by automating manual incident remediation processes, which in some cases can reduce MTTRs from hours down to seconds.

Here’s how that would work. It involves using the Ayehu platform as an integration hub in your environment. Ayehu would then connect to every system that needs to be interacted with when remediating an incident.

So for example, if your environment has a monitoring system like LogicMonitor, that’s where an incident will be detected first. And LogicMonitor, now integrated with Ayehu, will generate an alert which Ayehu will instantaneously intercept.

Ayehu will then parse that alert to determine what the underlying incident is, and launch an automated workflow to remediate that specific underlying incident.

As a first step in our workflow we’re going to automatically create a ticket in ServiceNow, BMC Remedy, JIRA, or any ITSM platform you prefer. Here again is where automation really shines over taking the manual approach, because letting the workflow handle the documentation will ensure that it gets done in a timely manner, in fact in real-time. Automation also ensures that documentation gets done thoroughly. Service Desk staff often don’t have the time or the patience to document every aspect of a resolution properly because they’re under such a heavy workload.

The next step, and actually this can be at any step within that workflow, is pausing its execution to notify and seek human approval for continuation. Just to illustrate why you might do this, let’s say that a workflow got triggered because LogicMonitor generated an alert that a server dropped below 10% free disk space. The workflow could then go and delete a bunch of temp files to free up space, it could compress a bunch of log files and move them somewhere else, and do all sorts of other things to free up space, but before it does any of that, the workflow can be configured to require human approval for any of those steps.

The human can either grant or deny approval so the workflow can continue on, and that decision can be delivered by laptop, smartphone, email, Instant Messenger, or even via a regular telephone. However, note that this notification/approval phase is entirely optional. You can also choose to put the workflow on autopilot and proceed without any human intervention. It’s all up to you, and either option is easy to implement.

Then the workflow can begin remediating the incident which triggered the alert.

As the remediation is taking place, Ayehu can update the service desk ticket in real-time by documenting every step of the incident remediation process.

Once the incident remediation is completed, Ayehu can automatically close the ticket.

And finally, it can go back into LogicMonitor and automatically dismiss the alert that triggered this entire process. This is how you can leverage intelligent automation to better manage alert storms, as well as simultaneously eliminating the potential for human error that can lead to outages in your environment.

Gartner concurs with this approach.

In a recently refreshed paper they published (ID G00336149 – April 11, 2019) one of their Vice-Presidents wrote that “The intricacy of access layer network decisions and the aggravation of end-user downtime are more than IT organizations can handle. Infrastructure and operations leaders must implement automation and artificial intelligence solutions to reduce mundane tasks and lost productivity.”

No ambiguity there.

Ayehu